There is a sex bias for common overuse running injuries that are associated with sex-specific hip kinematics. Gait retraining programs aimed at altering hip kinematics may be more efficient if they incorporated an understanding of how hip kinematics are correlated with the movement of the remaining body segments. We applied a principal component analysis to structure the whole-body running kinematics of 23 runners (12 ♀) into k = 12 principal movements (PMk), describing correlated patterns of upper and lower body movements. We compared the time-dependent movement amplitudes with respect to each PMk between males and females using a waveform analysis and interpreted our findings according to stick figure animations. The movement amplitudes of two PMs (PM6 and PM8) showed statistically significant effects of “sex,” which were independent of running speed. According to PM8, females showed more hip adduction, which correlated with increased transverse rotation of the pelvis and upper body compared to men. We propose that increased hip adduction and upper body rotation in female runners may be a strategy to compensate for a less efficient arm and upper body swing compared to men. Gait interventions aimed at reducing hip adduction and running-related injuries in female runners should consider instructions for both upper and lower body to maximize training efficacy.

A growing number of studies apply Principal Component Analysis (PCA) on whole-body kinematic data to facilitate an analysis of posture changes in human movement. An unanswered question is, how much the PCA outcomes depend on the chosen measurement device. This study aimed to assess the internal consistency of PCA outcomes from treadmill walking motion capture data simultaneously collected through laboratory-grade optical motion capture and field-suitable inertial-based motion tracking. Data was simultaneously collected using VICON (whole-body plug-in gait marker positions) and Xsens (body segment positions) from 20 participants during 2-min treadmill walking. Using PCA, Principal Movements (PMs) were determined using two commonly used practices: on an individual and a grouped basis. For both, correlation matrices were used to determine internal consistency between outcomes from either measurement system for each PM. Both individual and grouped approach showed excellent internal consistency between outcomes from the two systems among the lower order PMs. For the individual analysis, high correlations were only found along the diagonal of the correlation matrix while the grouped analysis also showed high off-diagonal correlations. These results have important implications for future application of PCA in terms of the independence of the resulting PM data, the way group-differences are expressed in higher-order PMs and the interpretation of movement complexity. Concluding, while PCA-outcomes from the two systems start to deviate in the higher order PMs, excellent internal consistency was found in the lower order PMs which already represent about 98% of the variance in the dataset.

Visual guidance of gait is an important skill for everyday mobility and for prevention of falls in older adults. While this has often been studied using eye-tracking techniques, recent studies have shown that visual exploration involves more than just the eye; head movement and potentially the whole body is involved for successful visual exploration. Here, we use Principal Component Analysis (PCA) to assess to what extend whole-body movement patterns are related to exploratory head movement during gait. Twenty-one (after exclusions) healthy young adult volunteers followed a treadmill walking protocol designed to elicit different types of head movements (no stimuli compared to stimuli requiring horizontal, vertical, and mixed gaze shifts). PCA was used to establish whole-body correlated patterns of marker movement (Principal Movements; PMs) related to the activity of the head. In total 37 higher order PMs were found to be associated with head movement, two of these showed significant differences between trials associated with strong head rotations in the horizontal and sagittal plane. Both of these were associated with a whole-body pattern of activity. It was found that an analysis of the higher order components was required to establish that exploratory head movements are associated with distinct movement patterns across the body. This shows that visual exploration can produce movement patterns that are at direct contrast with the alleged aim of the postural system (to minimize body movement as much as possible) since they could have a destabilizing effect on the body. These findings shed new light on established results in visual search research and hold relevance for fall and injury prevention.

Visual guidance of gait is an important skill for everyday mobility. While this has often been studied using eye-tracking techniques, recent studies have shown that visual exploration involves more than just the eye; head movement and potentially the whole body is involved for successful visual exploration. This study aimed to assess coordinative patterns associated with head movement and it was hypothesized that these patterns would span across the body, rather than being localized. Twenty-one (after exclusions) healthy young adult volunteers followed a treadmill walking protocol designed to elicit different types of head movements (no stimuli compared to stimuli requiring horizontal, vertical, and mixed gaze shifts). Principal Component Analysis was used to establish whole-body correlated patterns of marker movement (Principal Movements; PMs) related to the activity of the head. In total 37 higher order PMs were found to be associated with head movement, two of these showed significant differences between trials associated with strong head rotations in the horizontal and sagittal plane. Both of these were associated with a whole-body pattern of activity. An analysis of the higher order components revealed that exploratory head movements are associated with distinct movement patterns, which span across the body. This shows that visual exploration can produce whole-body movement patterns that have a potentially destabilizing influence. These findings shed new light on established results in visual search research and hold relevance for fall and injury prevention.

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